1. Field of the Invention
The present invention generally relates to methods and systems for estimating, monitoring and managing road traffic. More specifically, the present invention proposes a highly flexible method and system for monitoring and/or estimating and/or managing the road traffic.
2. Description of the Related Art
The estimation, monitoring and management of road traffic are normally accomplished based on a count of the number of vehicles that pass through one or more points of the monitored network of roads.
The vehicles counting methods are essentially of two types: manual counting methods and automatic counting methods.
Manual vehicles counting methods provide that operators, staying at the prescribed monitoring points along the roads, visually count the passing vehicles.
Automatic vehicles counting methods provide for placing, on or within the road floor, detectors adapted to detect the passage of the vehicles. Different types of detectors can be used, the more common being:                rubber pipes closed at an end and connected to a membrane at the other end; the passage of a vehicle over the pipe creates a pressure therein that causes the membrane to flex, determining the increase of a vehicles counter;        metal coils through which an electric current is made to flow that produces an electromagnetic field; the passage of a vehicle alters the electromagnetic field, and this event is detected causing the increase of a vehicles counter;        television cameras connected to automatic image recognition systems adapted to count the number of transiting vehicles.        
The manual counting, requiring the continuous presence of people at the road sections to be monitored, is used only for time-limited monitoring campaigns.
On the contrary, automatic vehicles counting methods are used for monitoring the road traffic for relatively long periods of time; however, the deployment of the detectors on the roads network and their connection to a central data processing server is very expensive, especially in medium and large urban areas, which are the scenarios where the road traffic monitoring, estimation and management is more useful.
A known alternative to the above-described vehicles counting methods makes use of a certain number of vehicles (called “floating cars”) equipped with a GPS receiver which regularly transmit to a service center its position and speed, thereby allowing the service center to estimate the road traffic.
This method is as well very expensive, and its effectiveness is closely related to the number of circulating vehicles equipped with GPS receiver, i.e. to the number of floating cars; due to this, continuous monitoring of all the main roads of a certain area may not be possible.
In recent years, cellular mobile telephony networks (cellular PLMNs—Public Land Mobile Networks) have also been used for the purposes of estimation, monitoring and management of the road traffic, thanks to the widespread presence of mobile phones among the population.
Systems that exploit cellular PLMNs for the estimation, monitoring and management of the road traffic can be classified according to the type of information on the position of the vehicles that they require for their operation.
In particular, a first class of systems requires a continuous and exact knowledge of the geographical position of the circulating vehicles. A system that requires this type of information is for instance described in WO 99/44183 A1. This document discloses a method for collecting information about traffic situations, i.e. about the current traffic situation and the optimum routes between any start position and any target, and for the purpose of utilizing a mobile phone network in a more efficient and expedient manner, suggests a method characterized by using information about motion and position of mobile phones or mobile communication equipment as input in the calculations thereof.
A second class of systems require the knowledge of the geographical positions in which handovers from cell to cell occur; the information about the handovers positions is obtained by means of known location techniques such as for instance UL-TOA (UpLink Time Of Arrival), E-OTD (Enhanced Observed Time Difference), CGI+TA (Cell Global Identity+Timing Advance), E-CGI+TA (Enhanced Cell Global Identity+Timing Advance). A system that requires this type of information is for example described in U.S. Pat. No. 5,657,487. This document describes a system for determining the location of a mobile station based upon measurable mobile data values such as those provided by mobile-assisted handoff (MAHO) procedures. The mobile stations make signal strength measurements of nearby base stations and return that information to the serving base station. A timing advance necessary to synchronize the mobile may also be determined. The signal strength measurements and the timing advance data then provide information to map to an estimated vehicle location. Since the mobiles are assumed to measure signal strength discretely, there may be several consecutive positions along a road which return identical mobile data. The road is thus segmented into constant segments which are consecutively indexed, and an association is established between the associated mobile data vector and the index. The process for location of a mobile consists of first finding the road for the mobile unit, then finding the position along the road. The mobile vector is sequentially input into a look up table or neural networks (one for each road in the sector) until an output coordinate pair actually lies near the corresponding road. From that point on, the input vector provides an index to a constant region along the road, so the mobile is unambiguously located as to which road, and to which segment along the road it occupies.
A third class of systems requires the knowledge of the identifiers of the cells among which the handovers occur. A system that requires this type of information is for instance described in US 2005/0227696 A1. This document describes a system and method that continuously extracts traffic load and speed on roads within the coverage area of a cellular network. The data is extracted directly from communications in a cellular network without using any external sensors. The method enables correlating a car to a road it travels on and determining its speed by using only the partial data that arrives to the cellular switch. The method consists of the following stages: A learn phase, which can include a vehicle(s) with a location device (say GPS system) travels across the covered routes within a designated area and collects the cellular data (cell handover sequences and signal strength reports) and location data in parallel. The accumulated data is then analyzed and processed to create the reference database. An operational stage is provided in which communications on the cellular network control channel are monitored continuously, and matched against the reference database in order to locate their route and speed. The route and speed data is used in order to create a traffic status map within the designated area and alarm in real time on traffic incidents. The data analysis and data base structure are done in a manner that will enable the following: Very fast, high reliability initial identification of the vehicle's route in the operational stage, based on handovers' cell ID only, very fast, high reliability follow up forward and backwards of the vehicle's route in the operational stage, and real time, high reliability Incident detection.
A fourth class of systems requires the knowledge of the identifiers of the cells in which the subscribers of the mobile telephony network make their calls. A system that needs this type of information is for example described in EP 0763807. This document discloses an estimation of traffic conditions on roads located in the radio coverage areas of a wireless communications network based on an analysis of real-time and past wireless traffic data carried on the wireless communications network. Data analyzed may include, for example, actual (current) and expected (past average) number of a) active-busy wireless end-user devices in one or more cells at a particular period of time, b) active-idle wireless end-user devices registered in a location area of the wireless communications network, c) amount of time spent by mobile end-user devices in one or more cells at a particular period of time.
A fifth class of systems requires the knowledge of the location area in which the subscribers of the mobile telephony network are situated. A system that requires this type of information is for instance described in WO 03/041031 A1. This document relates to collecting of traffic data with the aid of a mobile station network. Such areas are determined in the mobile station network, wherein the terminal equipment communicates with the network with the aid of one or more predetermined messages. Based on the message between the network and terminal equipment and relating to a first area a first time by the clock is stored, and based on the message between the network and the same terminal equipment and relating to a second area a second time by the clock is stored. The times by the clock are used in order to obtain traffic data by calculating, for example, the time spent on moving from one area to another. By determining the distance between areas along the road it is possible also to determine the speed of the vehicle. Information may also be collected to form a statistic distribution.
U.S. Pat. No. 6,587,781 discloses a method and system for modeling and processing vehicular traffic data and information, comprising: (a) transforming a spatial representation of a road network into a network of spatially interdependent and interrelated oriented road sections, for forming an oriented road section network; (b) acquiring a variety of the vehicular traffic data and information associated with the oriented road section network, from a variety of sources; (c) prioritizing, filtering, and controlling, the vehicular traffic data and information acquired from each of the variety of sources; (d) calculating a mean normalized travel time (NTT) value for each oriented road section of said oriented road section network using the prioritized, filtered, and controlled, vehicular traffic data and information associated with each source, for forming a partial current vehicular traffic situation picture associated with each source; (e) fusing the partial current traffic situation picture associated with each source, for generating a single complete current vehicular traffic situation picture associated with entire oriented road section network; (f) predicting a future complete vehicular traffic situation picture associated with the entire oriented road section network; and (g) using the current vehicular traffic situation picture and the future vehicular traffic situation picture for providing a variety of vehicular traffic related service applications to end users.
WO 07/077,472 discloses a road traffic monitoring system comprising: a first input (1a) for receiving position estimations of mobile terminals; a second input (1b) for receiving input specifications chosen depending on the type of service for which such monitoring is performed; and an output (1d) for generating road traffic maps, each road traffic map being associated with a set of territory elements and including, for each one of the territory elements, at least one mobility index of mobile terminals travelling within such territory element. Preferably, input specifications are chosen among at least two of the following parameters: territory element, territory element observation time slot, maximum allowable error on the estimation of said at least one mobility index.